Deep Learning with Structured Data

6 Training the model and running experiments

This chapter covers

• Viewing the end-to-end training process
• Selecting subsets of the dataset for training, validation, and testing
• Doing an initial training run
• Measuring the performance of your model
• Optimizing your training time by exploiting Keras’ early stopping feature
• Shortcuts to scoring
• Saving trained models
• Running a series of training experiments to improve model performance

So far in this book, we have prepared the data and examined the code that makes up the model itself. Now we are finally ready to train the model. We’ll review some of the basics, including selecting the training, test, and validation dataset. Then we’ll go through an initial training run to validate that the code ...